• Title/Summary/Keyword: Principle components analysis

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3-Dimensional Performance Optimization Model of Snatch Weightlifting

  • Moon, Young-Jin;Darren, Stefanyshyn
    • Korean Journal of Applied Biomechanics
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    • v.25 no.2
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    • pp.157-165
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    • 2015
  • Object : The goals of this research were to make Performance Enhanced Model(PE) taken the largest performance index (PI) through artificial variation of principle components calculated by principle component analysis for trial data, and to verify the effect through comparing kinematic factors between trial data (Raw) and PE. Method : Ten subjects (5 men, 5 women) were recruited and 80% of their maximal record was considered. The PI is a regression equation. In order to develop PE, we extracted Principle components from trial position data (by Principle Components Analysis (PCA)). Before PCA, we made 17 position data to 3 row matrix according to components. We calculated 3 eigen value (principle components) through PCA. And except Y (medial-lateral direction) component (because motion of Y component is small), principle components of X (anterior-posterior direction) and Z (vertical direction) components were changed as following. Changed principle components = principle components + principle components ${\times}$ k. After changing the each principle component, we reconstructed position data using the changed principle components and calculated performance index (PI). A Paired t-test was used to compare Raw data and Performance Enhanced Model data. The level of statistical significance was set at $p{\leq}0.05$. Result : The PI was significantly increased about 12.9kg at PE ($101.92{\pm}6.25$) when compared to the Raw data ($91.29{\pm}7.10$). It means that performance can be increased by optimizing 3D positions. The difference of kinematic factors as follows : the movement distance of the bar from start to lock out was significantly larger (about 1cm) for PE, the width of anterior-posterior bar position in full phase was significantly wider (about 1.3cm) for PE and the horizontal displacement toward the weightlifter after beginning of descent from maximal height was significantly greater (about 0.4cm) for PE. Additionally, the minimum knee angle in the 2-pull phase was significantly smaller (approximately 2.7cm) for the PE compared to that of the Raw. PE was decided at proximal position from the Raw (origin point (0,0)) of PC variation). Conclusion : PI was decided at proximal position from the Raw (origin point (0,0)) of PC variation). This means that Performance Enhanced Model was decided by similar motion to the Raw without a great change. Therefore, weightlifters could be accept Performance Enhanced Model easily, comfortably and without large stress. The Performance Enhance Model can provide training direction for athletes to improve their weightlifting records.

A Research on Improving the Evaluation Model for Management Innovative Enterprises (서비스 경영 혁신 기업 평가 모형의 개선 방안 연구)

  • Roh, Jae-Whak
    • International Commerce and Information Review
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    • v.12 no.4
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    • pp.279-302
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    • 2010
  • A better selection model on management innovative enterprises is needed since the Korean government provides multi benefits to those selected enterprises. However, the selection model's propriety is suspicious because of the shortage of consideration of assessment items. In particular, the most important two assessment items, strategy and performance are suspected of multicollinearity because of high correlation scores. No consideration on multicollinearity among those items leads to erroneous selection which doubly counts the same components with different item names. The principle component analysis is applied to factor out the uncorrelated items. Using the resulted principle components, the new estimations are carried out. The comparison between estimated results from using principle components and non principle components shows that the present selection model overly considers the performance items compared to the real effect of items, which is a result of multicollinearity between performance and strategy.

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Quality Assessment of Curcuma longa L. by Gas Chromatography-Mass Spectrometry Fingerprint, Principle Components Analysis and Hierarchical Clustering Analysis

  • Li, Ming;Zhou, Xin;Zhao, Yang;Wang, Dao-Ping;Hu, Xiao-Na
    • Bulletin of the Korean Chemical Society
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    • v.30 no.10
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    • pp.2287-2293
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    • 2009
  • Gas Chromatography-Mass Spectrometry (GC-MS) fingerprint analysis, Principle Components Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were introduced for quality assessment of Curcuma longa L. (C. longa). The GC-MS fingerprint method was developed and validated by analyzing 33 batches of samples of C. longa from different geographic locations. 18 chromatographic peaks were selected as characteristic peaks and their relative peak areas (RPA) were calculated for quantitative expression. Two principal components (PCs) were extracted by PCA. C. longa collected from Guizhou and Fujian were separated from other samples by PC1, capturing 71.83% of variance. While, PC2 contributed for their further separation, capturing 11.13% of variance. HCA confirmed the result of PCA analysis. Therefore, GC-MS fingerprint study with chemometric techniques provides a very flexible and reliable method for quality assessment of C. longa.

Distributed Video Compressive Sensing Reconstruction by Adaptive PCA Sparse Basis and Nonlocal Similarity

  • Wu, Minghu;Zhu, Xiuchang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2851-2865
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    • 2014
  • To improve the rate-distortion performance of distributed video compressive sensing (DVCS), the adaptive sparse basis and nonlocal similarity of video are proposed to jointly reconstruct the video signal in this paper. Due to the lack of motion information between frames and the appearance of some noises in the reference frames, the sparse dictionary, which is constructed using the examples directly extracted from the reference frames, has already not better obtained the sparse representation of the interpolated block. This paper proposes a method to construct the sparse dictionary. Firstly, the example-based data matrix is constructed by using the motion information between frames, and then the principle components analysis (PCA) is used to compute some significant principle components of data matrix. Finally, the sparse dictionary is constructed by these significant principle components. The merit of the proposed sparse dictionary is that it can not only adaptively change in terms of the spatial-temporal characteristics, but also has ability to suppress noises. Besides, considering that the sparse priors cannot preserve the edges and textures of video frames well, the nonlocal similarity regularization term has also been introduced into reconstruction model. Experimental results show that the proposed algorithm can improve the objective and subjective quality of video frame, and achieve the better rate-distortion performance of DVCS system at the cost of a certain computational complexity.

Statistical Analysis of Sewage Plant Operation (하수처리장 운전조건의 통계분석)

  • 이찬형;문경숙
    • Journal of Environmental Science International
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    • v.11 no.1
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    • pp.63-68
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    • 2002
  • In this study, we examined statistical analysis between sewage plant operations parameters and effluent quality We got six components from principle component analysis of the operation parameters and secondary effluent quality. 91.8% of the total variance was explained by the six components. The components were identified in the following order : 1) organic matter removal by aeration basin microbe, 2) settleability on secondary clarifier load, 3) removal of nutrients, 4) microbial number increasement and species diversity, 5) microbial activity in aeration basin, 6) oxidation in aeration basin.

A Study on the Classification of Islands by PCA ( I ) (PCA에 의한 도서분류에 관한 연구( I ))

  • 이강우
    • The Journal of Fisheries Business Administration
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    • v.14 no.2
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    • pp.1-14
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    • 1983
  • This paper considers a classification of the 88 islands located at Kyong-nam area in Korea, using by examples of 12 components of the islands. By means of principal component analysis 2 principle components were extracted, which explained a total of 73.7% of the variance. Using an eigen variable criterion (λ>1), no further principle components were discussed. Principal component 1 and 2 explained 63.4% and 10.3% of the total variance respectively, The representation of the unrelated factor scores along the first and second principal axes produced a new information with respect to the classification of the islands. Based upon the representation, 88 islands were classified into 6 groups i. e. A, B, C, D, E, and F according to similarity of the components among them in this paper. The "Group F" belongs to a miscellaneous assortment that does not fit into the logical category. category.

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A Study on the Pollution Sources of Simple water Supply Piped System using Statistical Analysis (통계적 분석을 이용한 간이급수시설의 오염원에 관한 연구)

  • 이홍근;김현용;백도현;김지영;이태호
    • Journal of environmental and Sanitary engineering
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    • v.14 no.2
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    • pp.56-67
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    • 1999
  • This study was performed to suggest the basic data and plans for the establishment of safe water supply plans in simple water supply piped system in the rural areas. In 4 different places, 24 points of water sources 36 points of taps from water sources were sampled. Of the whole 60 points, 55 points were ground water and 5 points were surface water. 14 items were measured for the analysis of water quality on each samples. The measured items were analyzed again by statistical method ; cluster analysis and principle components analysis. The results of this study are as followed. 1) In water quality analysis on water sources, 4 items, bacteria, E.coli, NH3-N and Fe exceed the standard. Of 24 points, 20 points(83%) on bacteria, 1 point(4%) on NH3-N and Fe exceed the standard. 2) In water quality analysis on near and remote taps, 4 items, bacteria, E.coli, NH3-N and Fe , exceed the standard. Of 36 points, 20 points (81%) on bactria, 1 pint(3%) on NH3-N and Fe exceed the standard. 3)Cluster analysis on water quality shows the differences by the kinds of water sources, geographical characteristics and distance from water sources. 4) Principle components analysis on ground water shows that Factor 1 and Factor 3 are natural fluctuation by the content of soil. Also, Factor 2 and Factor 4 are penetration of pollutants to underground. Therefore, it is needed to take deeper ground water in order to prevent from pollution in the areas which have ground water as water source . 5) Principle components analysis on surface water shows that Factor 1 is penetration of vacteria from surface to water source when rainfalls. Also, Factor 2 is fluctuation of water quality by the geographical characteristics. Therefore, the counterplans against non-point pollution source must be taken. Filtration and disinfection facilities are needed in the areas which have surface water as water source.

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An Approach for a Substitution Matrix Based on Protein Blocks and Physicochemical Properties of Amino Acids through PCA

  • You, Youngki;Jang, Inhwan;Lee, Kyungro;Kim, Heonjoo;Lee, Kwanhee
    • Interdisciplinary Bio Central
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    • v.6 no.4
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    • pp.3.1-3.10
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    • 2014
  • Amino acid substitution matrices are essential tools for protein sequence analysis, homology sequence search in protein databases and multiple sequence alignment. The PAM matrix was the first widely used amino acid substitution matrix. The BLOSUM series then succeeded the PAM matrix. Most substitution matrixes were developed by using the statistical frequency of substitution between each amino acid at blocks representing groups of protein families or related proteins. However, substitution of amino acids is based on the similarity of physiochemical properties of each amino acid. In this study, a new approach was used to obtain major physiochemical properties in multiple sequence alignment. Frequency of amino acid substitution in multiple sequence alignment database and selected attributes of amino acids in physiochemical properties database were merged. This merged data showed the major physiochemical properties through principle components analysis. Using factor analysis, these four principle components were interpreted as flexibility of electronic movement, polarity, negative charge and structural flexibility. Applying these four components, BAPS was constructed and validated for accuracy. When comparing receiver operated characteristic ($ROC_{50}$) values, BAPS scored slightly lower than BLOSUM and PAM. However, when evaluating for accuracy by comparing results from multiple sequence alignment with the structural alignment results of two test data sets with known three-dimensional structure in the homologous structure alignment database, the result of the test for BAPS was comparatively equivalent or better than results for prior matrices including PAM, Gonnet, Identity and Genetic code matrix.

Dynamic analysis of multi-functional maintenance platform based on Newton-Euler method and improved virtual work principle

  • Li, Dongyi;Lu, Kun;Cheng, Yong;Zhao, Wenlong;Yang, Songzhu;Zhang, Yu;Li, Junwei;Shi, Shanshuang
    • Nuclear Engineering and Technology
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    • v.52 no.11
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    • pp.2630-2637
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    • 2020
  • The structure design of divertor Multi-Functional Maintenance Platform (MFMP) actuated by hydraulic system for China Fusion Engineering Test Reactor (CFETR) was introduced in this paper. The model of MFMP was established according to maintenance requirements. In this paper, Newton-Euler method and the improved virtual work principle were used, the equivalent driving force of each actuator was obtained through the equivalent Jacobian inverse matrix derived from velocity relationship among the components. The accuracy of the model was verified by ADAMS simulation. The stability control of the heavy-duty components driven by hydraulic cylinders based on Newton-Euler method and improved virtual work principle was established.

Analysis of Linear Regression Model with Two Way Correlated Errors

  • Ssong, Seuck-Heun
    • Journal of the Korean Statistical Society
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    • v.29 no.2
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    • pp.231-245
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    • 2000
  • This paper considers a linear regression model with space and time data in where the disturbances follow spatially correlated error components. We provide the best linear unbiased predictor for the one way error components. We provide the best linear unbiased predictor for the one way error component model with spatial autocorrelation. Further, we derive two diagnostic test statistics for the assessment of model specification due to spatial dependence and random effects as an application of the Lagrange Multiplier principle.

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